The First Political-Ecological Database and Its Use in Episode Analysis

Abstract

Biodiversity loss is a consequence of socio-ecological processes. Observations on anthropogenic actions toward ecosystems coupled to observations on ecosystem metrics are needed to help understand these processes so that ecosystem management policies can be derived and implemented to curb such destruction. Such data needs to be maintained in searchable data portals. To this end, this article delivers a first-of-its-kind relational database of observations on coupled anthropogenic and ecosystem actions. This Ecosystem Management Actions Taxonomy (EMAT) database is founded on a taxonomy designed to support models of political-ecological processes. Structured query language scripts for building and querying these databases are described. The use of episodes in the construction of political-ecological theory is also introduced. These are frequently occurring sequences of political-ecological actions. Those episodes that test positive for causality can aid in improving a political-ecological theory by driving modifications to an attendant computational model so that it generates them. Two relational databases of political-ecological actions are described that are built from online news articles and published data on species abundance. The first concerns the management of the East African cheetah (Acinonyx jubatus) population, and the second is focused on the management of rhinoceroses (Ceratotherium simum) in South Africa. The cheetah database is used to study the political drivers of cheetah habitat loss, and the rhino database is used study the political drivers of rhino poaching. An EMAT database is a fundamental breakthrough because is provides a language for conservation science to identify the objects and phenomena that it is about. Therefore, maintaining political-ecological data in EMAT databases will advance conservation science and consequently, improve management policies that are based on that science.